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Found 17 papers, 7 papers with code
HyperMono: A Monotonicity-aware Approach to Hyper-Relational Knowledge Representation
This paper proposes the HyperMono model for hyper-relational knowledge graph completion, which realizes stage reasoning and qualifier monotonicity.
UniArk: Improving Generalisation and Consistency for Factual Knowledge Extraction through Debiasing
We hypothesize that simultaneously debiasing these objectives can be the key to generalisation over unseen prompts.
Multi-view Contrastive Learning for Entity Typing over Knowledge Graphs
Knowledge graph entity typing (KGET) aims at inferring plausible types of entities in knowledge graphs.
Instances and Labels: Hierarchy-aware Joint Supervised Contrastive Learning for Hierarchical Multi-Label Text Classification
Hierarchical multi-label text classification (HMTC) aims at utilizing a label hierarchy in multi-label classification.
Inductive Knowledge Graph Completion with GNNs and Rules: An Analysis
The task of inductive knowledge graph completion requires models to learn inference patterns from a training graph, which can then be used to make predictions on a disjoint test graph.
HyperFormer: Enhancing Entity and Relation Interaction for Hyper-Relational Knowledge Graph Completion
Hyper-relational knowledge graph completion (HKGC) aims at inferring unknown triples while considering its qualifiers.
Combining Global and Local Merges in Logic-based Entity Resolution
In the recently proposed Lace framework for collective entity resolution, logical rules and constraints are used to identify pairs of entity references (e. g. author or paper ids) that denote the same entity.
BUCA: A Binary Classification Approach to Unsupervised Commonsense Question Answering
Unsupervised commonsense reasoning (UCR) is becoming increasingly popular as the construction of commonsense reasoning datasets is expensive, and they are inevitably limited in their scope.
Transformer-based Entity Typing in Knowledge Graphs
We investigate the knowledge graph entity typing task which aims at inferring plausible entity types.
Type-aware Embeddings for Multi-Hop Reasoning over Knowledge Graphs
Multi-hop reasoning over real-life knowledge graphs (KGs) is a highly challenging problem as traditional subgraph matching methods are not capable to deal with noise and missing information.
A Description Logic for Analogical Reasoning
Ontologies formalise how the concepts from a given domain are interrelated.
Answering Regular Path Queries Over SQ Ontologies
We study query answering in the description logic $\mathcal{SQ}$ supporting qualified number restrictions on both transitive and non-transitive roles.
On Finite and Unrestricted Query Entailment beyond SQ with Number Restrictions on Transitive Roles
We study the description logic SQ with number restrictions applicable to transitive roles, extended with either nominals or inverse roles.
On Finite Entailment of Non-Local Queries in Description Logics
We study the problem of finite entailment of ontology-mediated queries.
Plausible Reasoning about EL-Ontologies using Concept Interpolation
In this paper, we instead propose an inductive inference mechanism which is based on a clear model-theoretic semantics, and can thus be tightly integrated with standard deductive reasoning.
Quantified Markov Logic Networks
Markov Logic Networks (MLNs) are well-suited for expressing statistics such as "with high probability a smoker knows another smoker" but not for expressing statements such as "there is a smoker who knows most other smokers", which is necessary for modeling, e. g. influencers in social networks.
From Knowledge Graph Embedding to Ontology Embedding? An Analysis of the Compatibility between Vector Space Representations and Rules
To address this shortcoming, in this paper we introduce a general framework based on a view of relations as regions, which allows us to study the compatibility between ontological knowledge and different types of vector space embeddings.
